444 search results - page 11 / 89 » Learning Nonlinear Dynamical Systems Using an EM Algorithm |
NIPS
2008
14 years 11 months ago
2008
Many nonlinear dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
101
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ECCB
2003
IEEE
15 years 3 months ago
2003
IEEE
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
ICAISC
2010
Springer
15 years 2 months ago
2010
Springer
In the paper we recover a Hammerstein system nonlinearity. Hammerstein systems, incorporating nonlinearity and dynamics, play an important role in various applications, and e¤ecti...
71
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GECCO
2005
Springer
15 years 3 months ago
2005
Springer
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
83
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ISNN
2007
Springer
15 years 3 months ago
2007
Springer
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...